code: def env_0():
      return Environment(
          train_dataset=get_toy_classification_data(),
          results_path=assets_dir,
          metrics=["roc_auc_score"],
          cv_type="RepeatedStratifiedKFold",
          cv_params=dict(n_splits=3, n_repeats=2, random_state=32),
      )
  
file_path: hyperparameter_hunter/tests/smoke_tests/test_xgboost.py
imports: from hyperparameter_hunter import Environment, CVExperiment, Real, Integer, Categorical
  from hyperparameter_hunter import RandomForestOptPro
  from hyperparameter_hunter.i_o.result_reader import has_experiment_result_file
  from hyperparameter_hunter.utils.learning_utils import get_toy_classification_data
  import pytest
  from xgboost import XGBClassifier
label_desc: Use image node_id 1 for calling a global function with example usage: env_0() and returns: Environment